Privacy and the Internet of Things

In light of a recent statement made by James Clapper, the US Director of National Intelligence, it has been made apparent that United States government and intelligence agencies maintain a stranglehold on surveillant practices, despite use of encryption and recent backlash by citizens regarding government privacy infringements. As reported by the Guardian, Clapper confirmed that Internet of Things devices allow for surveillant practices by intelligence agencies.
“In the future, intelligence services might use the [internet of things] for identification, surveillance, monitoring, location tracking, and targeting for recruitment, or to gain access to networks or user credentials,” explains James Clapper at his annual “assessment of threats” against the US (Guardian 2016).
This includes law enforcement agencies which have increasingly requested court orders which request companies to provide data collected from citizens. As noted by Trevor Timm, companies such as Fitbit and Dropcam, have been requested or have provided user data to legal authorities (Guardian 2016). What should be noted, is the type of information gathered by IoT devices, which fuels privacy concerns. Billions of IoT devices currently exist, “each of which are designed to harvest, store, and communicate a wealth of data” (Maras 2015:102). This data provides real-time information regarding a user’s “health and finances, locations, contacts, habits, behaviours, and activities” (Maras 2015:102) essentially mapping “patterns of life” (Amoore 2013:109). Very simply, the collected information by Internet of Things devices is, in effect, big data. Although never mentioned in any related literature as such, upon analyzing the content that the Internet of Things collects and comparing them to contemporary definitions of big data, distinct similarities can be drawn since data that is collected, “is more information than any individual human or group of humans can comprehend” (Andrejevic 2014:1675). Not to mention, several of these devices are vulnerable to hacking and other exploits.
As a result, a landscape has been created in which private information is constantly collected, stored, analyzed and monitored, as well as shared with a variety of other IoT devices, users and third parties (Maras 2015:102). Yet, users are potentially left without a full understanding of the implications of such a massive gathering of data. This excessive amount of data collection has raised several questions and concerns regarding privacy and surveillance. Users are not made aware of who benefits from this data, to whom this data is collected by, who it may be given to, when this data is collected and the potential outcomes of data collection. More than this, user profiling and targeting as well as social sorting are amongst other negative consequences of mass data gathering.
Although James Clapper’s statement is not a surprising revelation within the academic community, its importance lies in increasing public awareness regarding surveillant practices used by government and surveillance agencies. It brings to light how big data and IoT devices, which may provide many practical benefits, may, in some circumstances, be used to monitor citizens, and ultimately infringe on their privacy.
This results in a paradox where privacy and the Internet of Things cannot completely coexist (Wiseman 2013:8). There is a trade-off. In exchange for better, more feasible and more reliable services, a user must relinquish certain details about themselves. But, it must be reiterated that privacy is sacrificed in exchange for the tangible benefits offered by IoT devices. With this, a double edged sword is presented. With each incremental piece of information provided to Internet of Things devices and services, the better these services become. Yet, through this constant dissemination of private information, the more privacy is lost. Wiseman expresses how a technology which may not have initially been intended to pervade user privacy, may easily be reconfigured to ‘creep’ its users. “The purpose of the IoT to realize a smooth functioning information society may (also) turn into the perfect tool to realize a surveillance society” (Wiseman 2013:2). With such a vast amount of information, it is easy to understand how seemingly useful technology may actually be used as instruments for surveillance (Wiseman 2013:9).
IoT devices are starting to gain popularity as they begin to penetrate households, cities and various other aspects of day to day life. Thus, this public announcement by Clapper serves to inform citizens of the potential nefarious traits embodied in convenient gadgets.

Amoore, Louise 2013 ‘Security and the claim to privacy’ International Political Sociology8(2) 108-112
Andrejevic, Mark 2014. Big data, big questions “The Big Data Divide”. International Journal of Communication, 8(0):1673-1689

Maras 2015. “Internet of Things: Security and Privacy Implications” International Data Privacy Law 5(2):99-104

Timm, Trevor. 2016. “The government just admitted it will use smart home devices for spying” The Guardian Retrieved February 24, 2016 (http://www.theguardian.com/commentisfree/2016/feb/09/internet-of-things-smart-devices-spying-surveillance-us-government)

Wiseman, T.H.A. 2013. “Purpose and function creep by design: Transforming the face of surveillance through the Internet of Things”, European Journal of Law and Technology 4(2)

Picture: http://www.3g.co.uk/g_phones/large/internet-of-things-everything-you-need-to-know.jpg

A Call for Smart Policing in Toronto

Smart Policing Toronto feature image

Deputy Chief Peter Sloly believes the Toronto Police Service could reduce it’s force by ‘several hundred’ officers if it leverages technologies associated with ‘Big Data’ (CBC 2016). Sloly claims big changes are needed to restore trust in policing he feels is at a low point not just in Toronto, but also, across North America (Powell 2016). Investigations into the killing of Laquann McDonald by a Chicago police officer and Sammy Yatim by a Toronto police officer have damaged public perception and generated traction for calls for reform. In both cases, human resources management and new information communication technologies have been presented as solutions to the challenges of contemporary policing.

Many technology firms are making claims that advancements in data analytics can shift police forces from a reactive model to a predictive one. Through Big Data, the City of Chicago has produced a list of individuals that algorithms have categorized as high risk for committing serious crime. The Chicago Police Department (CPD) then contacted the individuals with information about the consequences of the criminal acts they were deemed likely to commit in an effort to change their ‘future’. At the IBM Smarter Cities conference in Las Vegas last year it was announced that Watson analytics would mine data provided by Twitter in an attempt to predict crime hot spots. 

Chicago, like Toronto, has a body worn camera pilot underway. Manuel launched the body worn camera pilot not long after the death of Laquan McDonald, claiming that the new technology would help restore faith and trust in the police force. Interestingly, the ‘in car camera’, an earlier form of mobile surveillance, was introduced twenty years prior in the State of Illinois with the same objective: restore the loss of faith and trust in local law enforcement. In some ways, these mobile cctv solutions are closer to the reactive policing model cited by Sloly. Although footage of interactions between officers and citizens has proven useful in both the McDonald and Yatim cases, the video is a record of reactive policing in action. 

Days after video of a Chicago Police Officer shooting Laquan McDonald sixteen times was released, Chicago Mayor Rahm Emanuel fired superintendent Garry F. McCarthy (Davey 2015). The footage was suppressed for a year after McDonald’s death, which, in conjunction with reports of officers deleting private CCTV footage at a nearby Burger King and threatening witnesses to make them file false accounts, fuelled outrage and protests in the city. In Toronto, just days after a verdict in the Sammy Yatim case was released, Mayor John Tory made a public appearance at the Toronto Police College. Tory observed training that focuses on dealing with people in crisis situations similar to Yatim’s case. Although the mayor was impressed he stated that more needed to be done to improve policing.

Like Tory, Sloly believes there is work to be done in the Toronto Police Force to foster new cultural norms. Sloly claims the practice of carding is reflective of a global crisis in policing. Research has repeatedly shown carding perpetuates systemic racial bias and is a result of inadequate training and supervision (Floyd v. State of New York; R. v. Fountain; Ontario Human Rights Commission 2003; Wortley and Owusu-Bempah 2011). In other words, officers were able to systematically target individuals for criminal investigation based on skin colour.

According to many creators of smart technologies, algorithms are not susceptible to bias (Kitchin 2014). Following this logic, a Big Data approach to policing could offer much to Toronto Police Services. However, scholars have contested the claims that algorithms ‘tell it like it is’ and encourage researchers to challenge claims of objectivity (van Dijck 2014). Transparency in the collection, sharing and analysis of data is an important safeguard against the potential failures of Big Data (Couldry and Powell 2014). These failures are already apparent in smart policing projects in the United States (Ferguson 2015). Thus, inadequate training and supervision of Big Data policing could reproduce the issues that have persisted with carding historically. Unfortunately, discussions about the potential for Big Data to erode democratic freedoms through the intensification of surveillance remain marginalized (Lyon 2014). Deputy Sloly, and those in the Toronto Police Service that favour his position, would do well to encourage researchers to join the table as the seemingly inevitable move to Big Data and smart policing occurs.

References:
CBC. (27012016). Police “trying to dissolve the uniform,” Tory says of crisis training. Retrieved February 3, 2016, from http://www.cbc.ca/news/canada/toronto/john-tory-police-college-1.3422033

Couldry, N., & Powell, A. (2014). Big Data from the bottom up. Big Data & Society, 1(2), 2053951714539277. http://doi.org/10.1177/2053951714539277

Davey, M. (2015, December 1). Chicago police superintendent fired in response to shocking video of black teen being shot 16 times. Retrieved from http://news.nationalpost.com/news/chicago-police-superintendent-fired-in-response-to-shocking-video-of-black-teen-being-shot-16-times

Ferguson, A. G. (2015). Big Data and Predictive Reasonable Suspicion. University of Pennsylvania Law Review, 163(2), 327–410.

Floyd v. State of New York. 82 Fed. R. Serv. 3d (West) 833 (S.D.N.Y. 2012).
Lyon, D. (2014). Surveillance, Snowden, and Big Data: Capacities, consequences, critique. Big Data & Society, 1(2). http://doi.org/10.1177/2053951714541861

Kitchin, R. (2014). Big Data, new epistemologies and paradigm shifts. Big Data & Society, 1(1), 2053951714528481. http://doi.org/10.1177/2053951714528481

Ontario Human Rights Commission. 2003. “Paying the Price: The Human Cost of Racial
Profiling.”

Powell, B. (2016, January 18). Passed over for the top job with Toronto police, Sloly says harnessing technology could allow the service to drop “several hundred police officers.” The Toronto Star. Retrieved from http://www.thestar.com/news/gta/2016/01/18/deputy-chief-peter-sloly-pushes-for-change-amid-low-point-and-looming-crisis.html

R. v. Fountain, 2013 ONCJ 434
van Dijck, J. (2014). Datafication, dataism and dataveillance: Big Data between scientific paradigm and ideology. Surveillance & Society, 12(2), 197–208.

Wortley, S. and Owusu-Bempah, A. 2011. “The usual suspects: police stop and search practices in
Canada.” Policing and Society 21(4):395-407.

Sixteen Shots: The Limits of Smart Tech in Urban Policing

Sixteen Shots The Limit of Smart Tech in Urban Policing

 

 

“I understand that the people will be upset and will want to protest when they see the video” Chicago Mayor Rahm Emanuel said before the release of footage showing the killing of 17 year old Laquan McDonald by a Chicago Police Officer (Guardian 2015). Emanuel has called for calm and framed the death as an opportunity to build bridges of understanding in a city plagued by racial profiling and police violence. The video was recorded a year ago by an in-car camera installed in a patrol car and clearly shows the youth being shot 16 times despite laying motionless on the road after the first bullet was fired. The Editorial Board of the Chicago Sun-Times says the video shows an officer “shoot down a young man as if he were a deer in the woods” (Chicago Sun-Times 2015).

The killing is astonishing on its own merits, here even more so in light of the fact that it took place in clear view of an in-car camera, ailment technology that has been in place for decades and is well known to the officers it records. The Chicago Editorial Board raises the incredulity of this killing taking place not in secret, not in a hidden location, but in clear and plain sight of other officers: “How is it than any Chicago police officer, right in front of at least eight other officers, would act in this way? Where is the weakness in the department’s training and supervision?” Despite several human and machine witnesses, Officer Van Dyke snuffed the life a youth with little inhibition stopping only when he ran out of bullets. Sixteen shots in total. In-car cameras did not save Laquan McDonald’s life, nor did they alter the behaviour of Officer Van Dyke. Yet the in-car camera was once a holy grail for police departments across the United States looking to ‘build trust’ with citizens in the wake of research showing racial profiling was prolific. That was over twenty years ago.

In the 1990s racial profiling had generated mistrust between police officers and citizens whose crimes were often nothing more than ‘being black while driving’ (Harris 2000). As research data proved the complaints of systemic racism had merit police chiefs and politicians were pressured to do something. Conveniently for businesses in the video recording industry, video recorders were getting smaller and more portable. Businesses saw an opportunity to develop a new market and ‘in-car camera’ pilot projects emerged in cities that could afford them. The first pilot in the State of Illinois started in 1991 (Koziol 1991). By the late 1990s, Gerald Arenberg, spokesman for the National Association of Chiefs of Police in Washington, D.C recognized that many police departments struggled to find the thousands of dollars needed per patrol car for in-car camera kits (Bucsko 1998). In 2002, the IACP was commissioned by the Department of Justice’s Office of Community Oriented Policing Services (COPS) to evaluate the impact of in-car camera usage on “officer conduct, management of the agencies and the public’s perception of police” (IACP 2003). The COPS agency had already made US$22 million in funding available for in-car camera kits across the nation. The report claimed ‘in-car cameras provided a substantial value to agencies using them’ on a range of measures including safety, accountability, training, performance and homeland security (IACP 2003:2). In-car cameras, the report suggested, were the holy grail of policing and much more.

One of the areas of concern identified in the IACP report was the management of data, specifically ‘storing, filing and retrieving video evidence’ (IACP 2003:2). Some departments would allow officers to self-manage data storage while other departments created positions for that task (Bucsko 1998). Relatedly, the issue of when video should be captured created tension for many departments. In the 90s, a police department in Florida requested the vendor override the design that allowed officers to turn the recording on and off so that the recording was perpetual (Mossman 1998). This was a rare request among several hundred clients according to the vendor, which created technical problems with the machinery and left officers feeling like they were being watched by big brother. Without control to turn the recording off and on at their discretion, the officers lost some of their autonomy. Including officers in the gaze of surveillance technology categorized them as a suspect population and reflects a shift in police supervision (Ericson and Haggerty 1997). A shift not welcomed in all departments. In Canada, then Chief of Police for Toronto Police Service Julian Fantino was outraged at Provincial policy that would mandate in-car cameras. Fantino called it a ‘hammer over the head of police officers’ whom he felt did not need to be monitored so closely because they could be trusted (Mackie 2003).

Historically, police reform has routinely been resisted by police sub-cultures that have “succeeded in undermining or diluting reforms that were implemented after a scandal” (Weitzer 2005:21). Research in the UK demonstrated early on that sub-cultural norms can and do support the circumventing of state efforts to record police behaviour using video cameras (Norris and Armstrong 1999). Researchers have argued that police operated video surveillance is more likely to be tampered with than systems run by other authorities (Goold 2003), calling into question who is protected ultimately by the adoption of new surveillance technology. The in-car camera footage of Laquan McDonald’s death was withheld from public viewing for a year under the thinly veiled pretence of further investigation (Friedersdorf 2015). This is typical of footage created by police forces, which according to Ben Brucato are “…most often used for their benefit and restricted from legal access by civilians or their attorneys” (2015:462). Moreover, Chicago Police officers allegedly accessed and deleted CCTV footage at a nearby Burger King moments after Laquan was killed (Guardian 2015).

Laquan McDonald was killed on a busy public road in front of several human and machine witnesses. The in-car camera footage paints a very grim picture of the potential for surveillance technology to create cultural change in policing. Yet, perhaps not surprisingly, a few months after Laquan’s death Mayor Emanuel announced a body worn camera pilot project for the City of Chicago, which he framed as a way to rebuild trust and to give citizens a sense of safety in the city (Spielman 2015). Purchasing more cameras may look promising on the surface, however, it side steps the real issue. Without a change in policing culture, more cameras will only produce more recordings of what the previous generation of cameras has captured.

Bibliography

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Bucsko, Mike. “Cost Limist Police Cameras 30 Percent of 119 County Departments Can Tape Incidents.” Pittsburgh Post-Gazette. October 7, 1998.
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Spielman, Fran. “Emanuel Launches Body-Cam Pilot to Rebuild Trust between Citizens and Police.” Chicago, January 1, 2015. http://chicago.suntimes.com/news-chicago/7/71/306307/emanuel-unveil-second-term-crime-agenda.
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